MiMo-V2.6-Flash
Parameters
309B
Context Length
1.05M
Modality
Multimodal
Architecture
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License
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Release Date
21 Sept 2026
Knowledge Cutoff
-
API Pricing (per 1M)
Input: $0.14 · Output: $0.28
System Requirements
VRAM requirements for different quantization methods and context sizes
1,024 tokens
Consumer
36x RTX 4090
24GB VRAM
Datacenter
10x NVIDIA A100
80GB VRAM
Apple Silicon
7x Apple M3 Max
128GB VRAM
1,048,576 tokens
Consumer
44x RTX 4090
24GB VRAM
Datacenter
12x NVIDIA A100
80GB VRAM
Apple Silicon
9x Apple M3 Max
128GB VRAM
Architecture Diagram
Evaluation Benchmarks
No evaluation benchmarks for MiMo-V2.6-Flash available.
Rankings
Overall Rank
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Coding Rank
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About MiMo-V2.6-Flash
MiMo-V2.6-Flash is an open-source multimodal mixture-of-experts foundation model developed by Xiaomi. With 309B total parameters activating 15B per token, it delivers high-efficiency performance across text, image, audio, and video inputs.
Technical Specifications
Attention
Attention Structure
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Attention Heads
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Key-Value Heads
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Attention Head Dimension
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Position Embedding
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RoPE Theta
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Sliding Window Attention
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Sliding Window Size
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Sliding Window Ratio
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Linear Attention
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Linear Attention Ratio
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Normalization
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Activation Function
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Dimensions
Auxiliary Parameters
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Hidden Dimension Size
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Number of Layers
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FFN Intermediate Size (Dense)
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Multi-Token Prediction Heads
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Tokenizer
Vocabulary Size
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Resources
About MiMo V2
MiMo-V2-Flash is a Mixture-of-Experts (MoE) model with hybrid attention architecture designed for high-speed reasoning and agentic workflows. It features Multi-Token Prediction (MTP) to achieve state-of-the-art performance while significantly reducing inference costs. The model is optimized for long-context modeling and efficient inference.